| 基于PCNN改进算法的手写体识别研究 |
| |
| 引用本文： | 温荷.基于PCNN改进算法的手写体识别研究[J].计算机科学,2016,43(2):316-318. |
| |
| 作者姓名： | 温荷 |
| |
| 作者单位： | 成都东软学院计算机科学与技术系 成都611844 |
| |
| 基金项目： | 本文受2014年四川省教育厅科研项目(14ZB0346),2013年成都东软学院科研项目(NEU2013-017)资助 |
| |
| 摘 要： | 脉冲神经网络(PCNN)被广泛应用于图像处理、模式识别等领域。提出了一种基于PCNN的凹点检测改进算法。首先改进神经元激励函数,并利用小波收缩法去噪,保持图像的层次性,然后通过凹点检测识别手写体。实验结果表明,提出的方法能有效提高手写字母的识别率,尤其是在噪声环境下,识别率得到大幅提升。
|
| 关 键 词： | PCNN 凹点检测 小波收缩 手写体识别 |
| 收稿时间： | 2014/12/21 0:00:00 |
| 修稿时间： | 2015/5/19 0:00:00 |
Study of Handwriting Recognition of Improved Algorithm Based on PCNN |
| |
| WEN He.Study of Handwriting Recognition of Improved Algorithm Based on PCNN[J].Computer Science,2016,43(2):316-318. |
| |
| Authors: | WEN He |
| |
| Affiliation: | Department of Computer Science and Technology,Chengdu Neusoft University,Chengdu 611844,China |
| |
| Abstract: | Pulse coupled neural network(PCNN)is widely used in image processing,pattern recognition and other fields.This paper presented an improved algorithm for foveation points detection based on PCNN.First,neuron excitation function is improved,and wavelet shrinkage method is applied in the image to reduce the noise,preserving the hie-rarchy of image.Then the handwriting is identified through the foveation points detection.The experimental results indicate that the method can effectively improve the recognition rate of handwritten letters.Especially in the noise environment,the recognition rate can be greatly improved. |
| |
| Keywords: | PCNN Foveation points detection Wavelet shrinkage Handwriting recognition |
|
|
点击此处可从《计算机科学》下载全文 |
|
